Processing high data rate streams in System S
High-performance stream processing is critical in many sense-and-respond application domains—from environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high-rate...
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Veröffentlicht in: | Journal of parallel and distributed computing 2011-02, Vol.71 (2), p.145-156 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | High-performance stream processing is critical in many
sense-and-respond application domains—from environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high-rate live streams. The central tenets of this work are the programming model, the workload splitting mechanisms, the code generation framework, and the underlying System S middleware and
Spade programming model. We demonstrate considerable scalability behavior coupled with low processing latency in a real-world financial trading application.
► The
split/aggregate/join architectural pattern is identified as a common template for implementing stream processing applications in different domains. ►
Per-group processing is proven as an effective means of optimizing the implementation of the split/aggregate/join pattern. ► System S and SPADE are employed to provide a comprehensive performance evaluation of per-group split/aggregate/join processing on a cluster of machines, using a financial engineering application as a case study. |
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ISSN: | 0743-7315 1096-0848 |
DOI: | 10.1016/j.jpdc.2010.08.007 |